← Business ideasBusiness ideas in julia programming and data science
What to build starts with what people already complain about, not with a guess. These are recurring problems in julia programming and data science — the kind a small, focused tool or a micro-SaaS could address — with a note on where to start and a rough read on how commercially valuable fixing it looks.
Many users are struggling with optimizing their Julia code for performance, often comparing it unfavorably to other languages like Python and C++. They are seeking advice on best practices, specific optimization techniques, and help from consultants to improve their code's efficiency.
- Create a guide on common optimization techniques in Julia
- Develop a consulting service for Julia code optimization
- Build a tool that analyzes Julia code for performance bottlenecks
- Host workshops or webinars on Julia performance optimization
Who has this problem: data scientists, scientific computing professionals, Julia developers, machine learning practitioners
Reason to be cautious: The posts may be biased towards those who are struggling, while satisfied users may not be voicing their experiences.
Pain pointTrend: NewConfidence: Low6 mentions · 1 communities · new
“Hi everyone, I am new to Julia and absolutely loving its speed and simplicity so far. However, as I start working on more complex projects…, I would like to ensure my code is as efficient as possible. I have read about Julia's impressive performance potential, but I am aware that achieving optima...” — julialang-discourse
“Hi All, I am doing some Monte Carlo computation using Python (compiling some functions to C++ using the Numba package). I thought I would see how Julia compares. As is good programming practice, I scraped some code from the Internet https://shinaoka.github.io/hpc_julia/docs/2dIsing.html Ising 2D ...” — julialang-discourse
Users frequently encounter long compilation times and installation errors when working with Julia packages, which hampers their productivity and leads to frustration. Many are seeking solutions to speed up the process and resolve compatibility issues.
- Create a tool to optimize package installation and precompilation times.
- Develop a troubleshooting guide for common installation errors.
- Build a community-driven database of package compatibility issues and solutions.
Who has this problem: Julia developers, Data scientists using Julia, New users of Julia
Pain pointTrend: NewConfidence: Low5 mentions · 1 communities · new
“Hi everyone, I've been using ModelingToolkit.jl on Google Colab recently, and I've run into a major issue: the compilation time is extremely large. In my case, the first-time compilation of ModelingToolkit took around 3,400–3,500 seconds (nearly an hour), which essentially makes the first run of ...” — julialang-discourse
“Hi all! Ever since working with GLMakie, GraphMakie etc, I've been having a LOT of issues with my packages in Julia, it takes really really long for them to precompile at the start [1] (which is not how it's been up until now), and I keep getting errors of methods not being found [2]. Yesterday I...” — julialang-discourse
Users are expressing concerns about the performance of Julia, particularly in comparison to other languages like Python. They are looking for ways to improve execution speed and efficiency in their applications.
- Develop a benchmarking tool to compare Julia's performance against other languages.
- Create a guide on optimizing Julia code for better performance.
- Offer consulting services for performance tuning in Julia applications.
Who has this problem: Data scientists, Researchers using Julia for numerical analysis, Developers transitioning from Python to Julia
Pain pointTrend: NewConfidence: Low3 mentions · 1 communities · new
“Hi everyone, I've been using ModelingToolkit.jl on Google Colab recently, and I've run into a major issue: the compilation time is extremely large. In my case, the first-time compilation of ModelingToolkit took around 3,400–3,500 seconds (nearly an hour), which essentially makes the first run of ...” — julialang-discourse
“Hello, I'm comparing the performance of Julia and Python for a specific task involving time series data and feature extraction. I've implemented a parallel computation in both languages and noticed that Python is significantly faster than Julia in this scenario. I am trying to understand why this...” — julialang-discourse
Users are facing challenges with Julia's module system and package management, leading to confusion and inefficiencies in their workflows. They are looking for clearer documentation and improvements in the module handling.
- Create a comprehensive guide on using Julia's module system effectively.
- Develop a tool to visualize module dependencies and conflicts.
- Host workshops to educate users on best practices for package management.
Who has this problem: Julia developers, New users of Julia, Researchers using Julia for scientific computing
Pain pointTrend: NewConfidence: Low3 mentions · 1 communities · new
“I know that there has been a lot of conversation in the past about this, but most of the questions end with a response like “in Julia 1.6 the loading time will be much better”. Since we are in Julia 1.6 I would like to again ask the question and if someone could identify the different factors tha...” — julialang-discourse
“Sukera: May I ask how long you’ve been around with julia? I certainly remember the days of 0.6, where e.g. using Plots took tens of minutes on the very machine I’m typing on now. Only since about a month. In my bachelor thesis of physics, I wrote rust and python and for my master thesis of physic...” — julialang-discourse